Search

We apply a high-resolution chemical transport model (GEOS-Chem CTM) with updated treatment of volatile organic compounds (VOCs) and a comprehensive suite of airborne datasets over North America to (i) characterize the VOC budget and (ii) test the ability of current models to capture the distribution and reactivity of atmospheric VOCs over this region. Biogenic emissions dominate the North American VOC budget in the model, accounting for 70 % and 95 % of annually emitted VOC carbon and reactivity, respectively. Based on current inventories anthropogenic emissions have declined to the point where biogenic emissions are the dominant summertime source of VOC reactivity even in most major North American cities. Methane oxidation is a 2x larger source of nonmethane VOCs (via production of formaldehyde and methyl hydroperoxide) over North America in the model than are anthropogenic emissions. However, anthropogenic VOCs account for over half of the ambient VOC loading over the majority of the region owing to their longer aggregate lifetime. Fires can be a significant VOC source episodically but are small on average. In the planetary boundary layer (PBL), the model exhibits skill in capturing observed variability in total VOC abundance (R 2 = 0:36) and reactivity (R 2 = 0:54). The same is not true in the free troposphere (FT), where skill is low and there is a persistent low model bias (~ 60 %), with most (27 of 34) model VOCs underestimated by more than a factor of 2. A comparison of PBL: FT concentration ratios over the southeastern US points to a misrepresentation of PBL ventilation as a contributor to these model FT biases. We also find that a relatively small number of VOCs (acetone, methanol, ethane, acetaldehyde, formaldehyde, isoprene C oxidation products, methyl hydroperoxide) drive a large fraction of total ambient VOC reactivity and associated model biases; research to improve understanding of their budgets is thus warranted. A source tracer analysis suggests a current overestimate of biogenic sources for hydroxyacetone, methyl ethyl ketone and glyoxal, an underestimate of biogenic formic acid sources, and an underestimate of peroxyacetic acid production across biogenic and anthropogenic precursors. Future work to improve model representations of vertical transport and to address the VOC biases discussed are needed to advance predictions of ozone and SOA formation.

Abstract. Organic aerosol (OA) is an important fraction of submicron aerosols. However,it is challenging to predict and attribute the specific organic compounds andsources that lead to observed OA loadings, largely due to contributions fromsecondary production. This is especially true for megacities surrounded bynumerous regional sources that create an OA background. Here, we utilizein situ gas and aerosol observations collected on board the NASA DC-8 duringthe NASA–NIER KORUS-AQ (Korea–United States Air Quality) campaign toinvestigate the sources and hydrocarbon precursors that led to the secondaryOA (SOA) production observed over Seoul. First, we investigate thecontribution of transported OA to total loadings observed over Seoul byusing observations over the Yellow Sea coupled to FLEXPART Lagrangiansimulations. During KORUS-AQ, the average OA loading advected into Seoul was∼1–3 µg sm−3. Second, taking this background intoaccount, the dilution-corrected SOA concentration observed over Seoul was∼140 µgsm-3ppmv-1 at 0.5 equivalent photochemicaldays. This value is at the high end of what has been observed in othermegacities around the world (20–70 µgsm-3ppmv-1 at 0.5equivalent days). For the average OA concentration observed over Seoul(13 µg sm−3), it is clear that production of SOA from locallyemitted precursors is the major source in the region. The importanceof local SOA production was supported by the following observations.(1) FLEXPART source contribution calculations indicate anyhydrocarbons with a lifetime of less than 1 day, which are shown to dominate theobserved SOA production, mainly originate from South Korea. (2) SOAcorrelated strongly with other secondary photochemical species, includingshort-lived species (formaldehyde, peroxy acetyl nitrate, sum of acyl peroxynitrates, dihydroxytoluene, and nitrate aerosol). (3) Results froman airborne oxidation flow reactor (OFR), flown for the first time, show afactor of 4.5 increase in potential SOA concentrations over Seoul versus overthe Yellow Sea, a region where background air masses that are advected intoSeoul can be measured. (4) Box model simulations reproduce SOAobserved over Seoul within 11 % on average and suggest that short-livedhydrocarbons (i.e., xylenes, trimethylbenzenes, and semi-volatile and intermediate-volatility compounds) were the main SOA precursors over Seoul. Toluenealone contributes 9 % of the modeled SOA over Seoul. Finally, along withthese results, we use the metric ΔOA/ΔCO2 toexamine the amount of OA produced per fuel consumed in a megacity, whichshows less variability across the world than ΔOA∕ΔCO.

Abstract. The evolution of organic aerosols (OAs) and their precursors in the boundary layer (BL) of the Colorado Front Range during the Front Range Air Pollution and Photochemistry Éxperiment (FRAPPÉ, July–August 2014) was analyzed by in situ measurements and chemical transport modeling. Measurements indicated significant production of secondary OA (SOA), with enhancement ratio of OA with respect to carbon monoxide (CO) reaching 0.085±0.003 µg m−3 ppbv−1. At background mixing ratios of CO, up to  ∼  1.8 µg m−3 background OA was observed, suggesting significant non-combustion contribution to OA in the Front Range. The mean concentration of OA in plumes with a high influence of oil and natural gas (O&G) emissions was  ∼  40 % higher than in urban-influenced plumes. Positive matrix factorization (PMF) confirmed a dominant contribution of secondary, oxygenated OA (OOA) in the boundary layer instead of fresh, hydrocarbon-like OA (HOA). Combinations of primary OA (POA) volatility assumptions, aging of semi-volatile species, and different emission estimates from the O&G sector were used in the Weather Research and Forecasting model coupled with Chemistry (WRF-Chem) simulation scenarios. The assumption of semi-volatile POA resulted in greater than a factor of 10 lower POA concentrations compared to PMF-resolved HOA. Including top-down modified O&G emissions resulted in substantially better agreements in modeled ethane, toluene, hydroxyl radical, and ozone compared to measurements in the high-O&G-influenced plumes. By including emissions from the O&G sector using the top-down approach, it was estimated that the O&G sector contributed to

Abstract. Chemical models must correctly calculate the ozone formation rate, P(O3), to accurately predict ozone levels and to test mitigation strategies. However, air quality models can have large uncertainties in P(O3) calculations, which can create uncertainties in ozone forecasts, especially during the summertime when P(O3) is high. One way to test mechanisms is to compare modeled P(O3) to direct measurements. During summer 2014, the Measurement of Ozone Production Sensor (MOPS) directly measured net P(O3) in Golden, CO, approximately 25 km west of Denver along the Colorado Front Range. Net P(O3) was compared to rates calculated by a photochemical box model that was constrained by measurements of other chemical species and that used a lumped chemical mechanism and a more explicit one. Median observed P(O3) was up to a factor of 2 higher than that modeled during early morning hours when nitric oxide (NO) levels were high and was similar to modeled P(O3) for the rest of the day. While all interferences and offsets in this new method are not fully understood, simulations of these possible uncertainties cannot explain the observed P(O3) behavior. Modeled and measured P(O3) and peroxy radical (HO2 and RO2) discrepancies observed here are similar to those presented in prior studies. While a missing atmospheric organic peroxy radical source from volatile organic compounds co-emitted with NO could be one plausible solution to the P(O3) discrepancy, such a source has not been identified and does not fully explain the peroxy radical model–data mismatch. If the MOPS accurately depicts atmospheric P(O3), then these results would imply that P(O3) in Golden, CO, would be NOx-sensitive for more of the day than what is calculated by models, extending the NOx-sensitive P(O3) regime from the afternoon further into the morning. These results could affect ozone reduction strategies for the region surrounding Golden and possibly other areas that do not comply with national ozone regulations. Thus, it is important to continue the development of this direct ozone measurement technique to understand P(O3), especially under high-NOx regimes.

The Korea-United States Air Quality Study (KORUS-AQ) conducted during May-June 2016 offered the first opportunity to evaluate direct-sun observations of formaldehyde (HCHO) total column densities with improved Pandora spectrometer instruments. The measurements highlighted in this work were conducted both in the Seoul megacity area at the Olympic Park site (37.5232° N, 27.1260° E; 26 ma.s.l.) and at a nearby rural site downwind of the city at the Mount Taehwa research forest site (37.3123° N, 127.3106° E; 160ma.s.l.). Evaluation of these measurements was made possible by concurrent ground-based in situ observations of HCHO at both sites as well as overflight by the NASA DC-8 research aircraft. The flights provided in situ measurements of HCHO to characterize its vertical distribution in the lower troposphere (0-5km). Diurnal variation in HCHO total column densities followed the same pattern at both sites, with the minimum daily values typically observed between 6:00 and 7:00 local time, gradually increasing to a maximum between 13:00 and 17:00 before decreasing into the evening. Pandora vertical column densities were compared with those derived from the DC-8 HCHO in situ measured profiles augmented with in situ surface concentrations below the lowest altitude of the DC-8 in proximity to the ground sites. A comparison between 49 column densities measured by Pandora vs. aircraft-integrated in situ data showed that Pandora values were larger by 16% with a constant offset of 0.22DU (Dobson units; R 2 = 0.68). Pandora HCHO columns were also compared with columns calculated from the surface in situ measurements over Olympic Park by assuming a well-mixed lower atmosphere up to a ceilometer-measured mixed-layer height (MLH) and various assumptions about the small residual HCHO amounts in the free troposphere up to the tropopause. The best comparison (slope = 1.03±0.03; intercept = 0.29±0.02DU; and R 2 = 0.78±0.02) was achieved assuming equal mixing within ceilometer-measured MLH combined with an exponential profile shape. These results suggest that diurnal changes in HCHO surface concentrations can be reasonably estimated from the Pandora total column and information on the mixed-layer height. More work is needed to understand the bias in the intercept and the slope relative to columns derived from the in situ aircraft and surface measurements.

Formaldehyde (HCHO) column data from satellites are widely used as a proxy for emissions of volatile organic compounds (VOCs) but validation of the data has been extremely limited. Here we use highly accurate HCHO aircraft observations from the NASA SEAC 4 RS campaign over the Southeast US in August-September 2013 to validate and intercompare six retrievals of HCHO columns from four different satellite instruments (OMI, GOME2A, GOME2B and OMPS) and three different research groups. The GEOS-Chem chemical transport model is used as a common intercomparison platform. All retrievals feature a HCHO maximum over Arkansas and Louisiana, consistent with the aircraft observations and reflecting high emissions of biogenic isoprene. The retrievals are also interconsistent in their spatial variability over the Southeast US ( r =0.4-0.8 on a 0.5°×0.5° grid) and in their day-to-day variability ( r =0.5-0.8). However, all retrievals are biased low in the mean by 20-51%, which would lead to corresponding bias in estimates of isoprene emissions from the satellite data. The smallest bias is for OMI-BIRA, which has high corrected slant columns relative to the other retrievals and low scattering weights in its air mass factor ( AMF ) calculation. OMI-BIRA has systematic error in its assumed vertical HCHO shape profiles for the AMF calculation and correcting this would eliminate its bias relative to the SEAC 4 RS data. Our results support the use of satellite HCHO data as a quantitative proxy for isoprene emission after correction of the low mean bias. There is no evident pattern in the bias, suggesting that a uniform correction factor may be applied to the data until better understanding is achieved.